model.predict_proba is not working in scoring script for classification

**This is run function. But My output of test data is class only not probabilities.**
@input_schema('data', PandasParameterType(input_sample))
@output_schema(NumpyParameterType(output_sample))
def run(data):
result=model.predict_proba(data)
return result.tolist()

**My deployement Function for reference**
deployment = ManagedOnlineDeployment(
name=deployment_name,
endpoint_name=online_endpoint_name,
model=registered_model.id,
instance_type="Standard_F4s_v2",
instance_count=1,
code_configuration=CodeConfiguration(
code="./artifact_downloads/outputs",
scoring_script="scoring_script.py",
),
liveness_probe=ProbeSettings(
failure_threshold=30,
success_threshold=1,
timeout=2,
period=10,
initial_delay=2000,
),
readiness_probe=ProbeSettings(
failure_threshold=10,
success_threshold=1,
timeout=10,
period=10,
initial_delay=2000,
),
)

從 scoring_script.py 開始，尤其檢查 run 函式及其輸入／輸出 schema，然後檢查 ManagedOnlineDeployment CodeConfiguration。使用所示的 model.predict_proba 呼叫重現已部署的請求，並將其回應與本機結果進行比較。當已部署 scoring 的回應包含類別機率，而不只是類別標籤時，即表示完成。

由索引模型根據 Issue 內容生成。